The winter North Atlantic Oscillation downstream teleconnection: insights from large-ensemble climate model simulations
The winter North Atlantic Oscillation (NAO) is the dominant pattern of atmospheric circulation variability over the North Atlantic region. It influences climate and weather such as surface air temperatures downstream over Eurasia through establishing a large-scale teleconnection, but past studies on...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ade4dc |
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| Summary: | The winter North Atlantic Oscillation (NAO) is the dominant pattern of atmospheric circulation variability over the North Atlantic region. It influences climate and weather such as surface air temperatures downstream over Eurasia through establishing a large-scale teleconnection, but past studies on the NAO’s downstream teleconnection have been largely limited to observational data, and further evidence of downstream impacts and associated mechanisms from comprehensive climate modeling is desirable. This study quantifies and analyzes this teleconnection on an interannual timescale by using both ERA5 reanalysis, and five large ensembles from four climate simulation models. A particular focus is placed on dynamical pathways, as well as variability among ensemble members that modulates the teleconnection strength. Results suggest that NAO signals are propagated downstream by Rossby waves, efficiently transmitted through waveguides along both the polar and subtropical jet streams to Eastern Eurasia; while heat can be advected weakly from upstream, advection plays a rather local effect inducing temperature anomalies from the Pacific Ocean onshore. Multiple linear regression shows that internal climate variability significantly modulates the teleconnection: a more locally dominant NAO pattern, and narrower waveguides could strengthen the teleconnection. These two factors combine to explain up to 70% of variance in the teleconnection strength, with each contributing almost equally. Reanalysis data marginally agree with the regression model (1.9 standardized residuals higher in strength), suggesting potential model biases in jets and the NAO variability. Monitoring these modulating factors would be crucial to understanding downstream climate predictability and improving climate prediction models linked to the NAO. |
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| ISSN: | 1748-9326 |